Search Results for author: Rakesh Nagi

Found 3 papers, 1 papers with code

xER: An Explainable Model for Entity Resolution using an Efficient Solution for the Clique Partitioning Problem

no code implementations NAACL (TrustNLP) 2021 Samhita Vadrevu, Rakesh Nagi, JinJun Xiong, Wen-mei Hwu

In this paper, we use Clique Partition- ing Problem (CPP), which is an Integer Pro- gram (IP) to formulate ER as a graph partition- ing problem and then highlight the explainable nature of this method.

Entity Resolution graph partitioning

At-Scale Sparse Deep Neural Network Inference with Efficient GPU Implementation

1 code implementation28 Jul 2020 Mert Hidayetoglu, Carl Pearson, Vikram Sharma Mailthody, Eiman Ebrahimi, JinJun Xiong, Rakesh Nagi, Wen-mei Hwu

This paper presents GPU performance optimization and scaling results for inference models of the Sparse Deep Neural Network Challenge 2020.

Risk-Averse Explore-Then-Commit Algorithms for Finite-Time Bandits

no code implementations30 Apr 2019 Ali Yekkehkhany, Ebrahim Arian, Mohammad Hajiesmaili, Rakesh Nagi

In this paper, we study multi-armed bandit problems in explore-then-commit setting.

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